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Testing convexity of a discrete distribution

Author

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  • Balabdaoui, Fadoua
  • Durot, Cécile
  • Koladjo, Babagnidé François

Abstract

Based on the convex least-squares estimator, we propose two different procedures for testing convexity of a probability mass function supported on N with an unknown finite support. The procedures are shown to be asymptotically calibrated.

Suggested Citation

  • Balabdaoui, Fadoua & Durot, Cécile & Koladjo, Babagnidé François, 2018. "Testing convexity of a discrete distribution," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 8-13.
    • Handle: RePEc:eee:stapro:v:137:y:2018:i:c:p:8-13
    DOI: 10.1016/j.spl.2017.10.023
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    References listed on IDEAS

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    1. Cécile Durot & Sylvie Huet & François Koladjo & Stéphane Robin, 2015. "Nonparametric species richness estimation under convexity constraint," Environmetrics, John Wiley & Sons, Ltd., vol. 26(7), pages 502-513, November.
    2. Chee, Chew-Seng & Wang, Yong, 2016. "Nonparametric estimation of species richness using discrete k-monotone distributions," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 107-118.
    3. Durot, Cécile & Huet, Sylvie & Koladjo, François & Robin, Stéphane, 2013. "Least-squares estimation of a convex discrete distribution," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 282-298.
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    Cited by:

    1. Balabdaoui, Fadoua & Kulagina, Yulia, 2020. "Completely monotone distributions: Mixing, approximation and estimation of number of species," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).

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